Transformer differential protection using wavelet transform

Özgönenel O., Karagöl S.

ELECTRIC POWER SYSTEMS RESEARCH, cilt.114, ss.60-67, 2014 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 114
  • Basım Tarihi: 2014
  • Doi Numarası: 10.1016/j.epsr.2014.04.008
  • Dergi Adı: ELECTRIC POWER SYSTEMS RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.60-67
  • Anahtar Kelimeler: Entropy approach, Minimum description length criterion, Inrush current, Internal fault, Power transformer, Wavelet packet analysis, ARTIFICIAL NEURAL-NETWORK, POWER TRANSFORMERS, IMPROVED OPERATION, INTERNAL FAULTS, CLASSIFICATION
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

This paper will propose a cascade of minimum description length criterion with entropy approach along with artificial neural network (ANN) as an optimal feature extraction and selection tool for a wavelet packet transform based transformer differential protection. The proposed protection method provides a reliable and computationally efficient tool for distinguishing between internal faults and inrush currents. The role of minimum description length criterion with entropy approach has been found to improve the efficiency of ANN with the dimensionality reduction of the feature vector. This reduction plays a major role in preventing the redundancy effect that can occur when using several features in an intelligent based monitoring system. (C) 2014 Elsevier B.V. All rights reserved.